A new hybrid framework for probabilistic wind speed prediction using deep feature selection and multi-error modification-Reference-Cited by-同舟云学术

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A new hybrid framework for probabilistic wind speed prediction using deep feature selection and multi-error modification

Published:2019-11 Issue: Volume:199 Page:111981
ISSN:0196-8904
Container-title:Energy Conversion and Management
language:en
Short-container-title:Energy Conversion and Management

Author:

Jiang Yan,Zhao Ning,Peng Liuliu,Liu Shuoyu

Funder

China Postdoctoral Science Foundation

National Natural Science Foundation of China

Doctoral Funding of Southwest University

Publisher

Elsevier BV

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Reference42 articles.

1. A review on recent size optimization methodologies for standalone solar and wind hybrid renewable energy system;Al-Falahi;Energy Convers Manage,2017

2. A two-stage data envelopment analysis model for efficiency assessments of 39 state’s wind power in the United States;Sağlam;Energy Convers Manage,2017

3. A review on the forecasting of wind speed and generated power;Lei;Renew Sustain Energy Rev,2009

4. A hybrid approach based on the Gaussian process with t-observation model for short-term wind speed forecasts;Hu;Renewable Energy,2017

5. Wind speed prediction model using singular spectrum analysis, empirical mode decomposition and convolutional support vector machine;Mi;Energy Convers Manage,2019

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2. Transient surface pressure of a rectangular cylinder subjected to downburst-like winds;Physics of Fluids;2024-08-01

3. Spatio-temporal prediction of total energy consumption in multiple regions using explainable deep neural network;Energy;2024-08

4. Wind Speed Probability Density Forecast Using Optimization Based Kernel Density Estimation and Quantile Regression;2024 IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems (ICITEICS);2024-06-28

5. Study on the distribution of average wind speeds at a mountainous bridge site for structural durability design;Advances in Bridge Engineering;2024-05-15

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